Effects of Fe content and natural aging on the microstructures and mechanical properties of recyclable heat treatment-free Al-7Si-0.3Mg die-cast alloys determined using machine learning
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OpenAlex topics: Aluminum Alloy Microstructure Properties · Aluminum Alloys Composites Properties · Magnesium Alloys: Properties and Applications
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References (45)
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1. Dong XX, Zhu X, Ji A (2019) Effect of super vacuum assisted high pressure die casting on the repeatability of mechanical properties of Al-Si-Mg-Mn die-cast alloys. J Mater Process Technol 266:105–113. https://doi.org/10.1016/j.jmatprotec.2018.10.03010.1016/j.jmatprotec.2018.10.030 ↗
2. Niu Z, Liu G, Li T et al (2022) Effect of high pressure die casting on the castability, defects and mechanical properties of aluminium alloys in extra-large thin-wall castings. J Mater Process Technol 303:1–13. https://doi.org/10.1016/j.jmatprotec.2022.11752510.1016/j.jmatprotec.2022.117525 ↗
3. Czerwinski F (2021) Current trends in automotive lightweighting strategies and materials. Materials 14:6631. https://doi.org/10.3390/ma1421663110.3390/ma14216631 ↗
4. Luo AA, Sachdev AK, Apelian D (2022) Alloy development and process innovations for light metals casting. J Mater Process Technol 306:117606. https://doi.org/10.1016/j.jmatprotec.2022.11760610.1016/j.jmatprotec.2022.117606 ↗
5. Hu R, Guo C, Ma M (2022) A study on high strength, high plasticity, non-heat treated die-cast aluminium alloy. Materials 15:295. https://doi.org/10.3390/ma1501029510.3390/ma15010295 ↗
6. Yuan LY, Han PW, Asghar G et al (2021) Development of high strength and toughness non-heated Al-Mg-Si alloys for high-pressure die-casting. Acta Metall Sin (Engl Lett) 34:845–860. https://doi.org/10.1007/s40195-020-01174-110.1007/s40195-020-01174-1 ↗
7. Zhu HY, Xia CJ, Zhang HW et al (2024) Design of non-heat treatable high pressure die casting Al alloys: a review. J Mater Eng Perform 33:8601–8626. https://doi.org/10.1007/s11665-024-09477-510.1007/s11665-024-09477-5 ↗
8. Dong XX, Yang H, Zhu X (2019) High strength and ductility aluminium alloy processed by high pressure die casting. J Alloy Compd 773:86–96. https://doi.org/10.1016/j.jallcom.2018.09.26010.1016/j.jallcom.2018.09.260 ↗
9. Zhang W, Xu J (2022) Advanced lightweight materials for automobiles: a review. Mater Des 221:110994. https://doi.org/10.1016/j.matdes.2022.11099410.1016/j.matdes.2022.110994 ↗
10. Zhao H, Yin Y, Wu Y (2024) How solute atoms control aqueous corrosion of Al-alloys. Nat Commun 15:561. https://doi.org/10.1038/s41467-024-44802-510.1038/s41467-024-44802-5 ↗
11. Lu Q, Wang J, Li H (2023) Synergy of multiple precipitate/matrix interface structures for a heat resistant high-strength Al alloy. Nat Commun 14:2959. https://doi.org/10.1038/s41467-023-38730-z10.1038/s41467-023-38730-z ↗
12. Jiao XY, Liu YX, Wang J et al (2023) The microstructure characteristics and fracture behavior of the polyhedral primary iron-rich phase and plate-shaped eutectic iron-rich phase in a high-pressure die-cast AlSi10MnMg alloy. J Mater Sci Technol 140:201–209. https://doi.org/10.1016/j.jmst.2022.09.01410.1016/j.jmst.2022.09.014 ↗
13. Dong XX, Youssef H, Zhu X (2021) High as-cast strength die-cast AlSi9Cu2Mg alloy prepared by nanoparticle strengthening with industrially acceptable ductility. J Alloy Compd 852:156873. https://doi.org/10.1016/j.jallcom.2020.15687310.1016/j.jallcom.2020.156873 ↗
14. Dong XX, Youssef H, Zhang Y (2019) High performance Al/TiB2 composites fabricated by nanoparticle reinforcement and cutting-edge super vacuum assisted die casting process. Compos B Eng 177:107453. https://doi.org/10.1016/j.compositesb.2019.10745310.1016/j.compositesb.2019.107453 ↗
15. Dong XX, Youssef H, Zhang Y (2020) Advanced heat treated die-cast aluminium composites fabricated by TiB2 nanoparticle implantation. Mater Des 186:108372. https://doi.org/10.1016/j.matdes.2019.10837210.1016/j.matdes.2019.108372 ↗
16. Yu W, He H, Zhang W (2020) Modulation of the natural aging effect on subsequent artificial aging in Al-Mg-Si aluminum alloys with alloying content ∼1 wt% through temperature tuning. J Alloy Compd 814:152277. https://doi.org/10.1016/j.jallcom.2019.15227710.1016/j.jallcom.2019.152277 ↗
17. Engler O, Marioara CD, Aruga Y (2019) Effect of natural ageing or pre-ageing on the evolution of precipitate structure and strength during age hardening of Al-Mg-Si alloy AA 6016. Mater Sci Eng A 759:520–529. https://doi.org/10.1016/j.msea.2019.05.07310.1016/j.msea.2019.05.073 ↗
18. Shishido H, Aruga Y, Murata Y (2022) Evaluation of precipitates and clusters during artificial ageing of two model Al-Mg-Si alloys with different Mg/Si ratios. J Alloy Compd 927:166978. https://doi.org/10.1016/j.jallcom.2022.16697810.1016/j.jallcom.2022.166978 ↗
19. Aruga Y, Kim SN, Kozuka M (2018) Effects of cluster characteristics on two-step ageing behaviour in Al-Mg-Si alloys with different Mg/Si ratios and natural ageing periods. Mater Sci Eng A 718:371–376. https://doi.org/10.1016/j.msea.2018.01.08610.1016/j.msea.2018.01.086 ↗
20. Shabestari SG (2004) The effect of iron and manganese on the formation of intermetallic compounds in aluminum-silicon alloys. Mater Sci Eng A 383:289–298. https://doi.org/10.1016/j.msea.2004.06.02210.1016/j.msea.2004.06.022 ↗
21. He Q, Zhang G, Zhang S (2024) Microstructural characterization of recycled Al-Mg-Si-based alloys upon the synergistic effect of ultrasonic technology (UT) and novel refiners. J Mater Res Technol 31:481–495. https://doi.org/10.1016/j.jmrt.2024.06.01410.1016/j.jmrt.2024.06.014 ↗
22. Moodispaw MP, Cinkilic E, Miao J (2024) The beneficial effect of iron in aluminum-cerium-based cast alloys. Metall Mater Trans A 55:1351–1362. https://doi.org/10.1007/s11661-024-07333-810.1007/s11661-024-07333-8 ↗
23. Raabe D, Ponge D, Uggowitzer PJ (2022) Making sustainable aluminum by recycling scrap: the science of dirty alloys. Prog Mater Sci 128:100947. https://doi.org/10.1016/j.pmatsci.2022.10094710.1016/j.pmatsci.2022.100947 ↗
24. Shaha SK, Czerwinski F, Kasprzak W et al (2016) Effect of Mn and heat treatment on improvements in static strength and low-cycle fatigue life of an Al-Si-Cu-Mg alloy. Mater Sci Eng A 657:441–452. https://doi.org/10.1016/j.msea.2016.01.01510.1016/j.msea.2016.01.015 ↗
25. Biswas P, Raj A, Neelakantan S et al (2025) Wear micromechanics, mechanisms, and wear map of Al-12.6Si-0.25Fe-x Mn alloy: the role of Al15(Mn, Fe)3Si2 intermetallic and microstructure modification. ASME J Tribol March 147:031702. https://doi.org/10.1115/1.406686810.1115/1.4066868 ↗
26. Zhang X, Chen Y, Hu J (2018) Recent advances in the development of aerospace materials. Prog Aerosp Sci 97:22–34. https://doi.org/10.1016/j.paerosci.2018.01.00110.1016/j.paerosci.2018.01.001 ↗
27. Miller WS, Zhuang L, Bottema J (2000) Recent development in aluminium alloys for the automotive industry. Mater Sci Eng A 280:37–49. https://doi.org/10.1016/S0921-5093(99)00653-X10.1016/S0921-5093(99)00653-X ↗
28. Curtarolo S, Hart GLW, Nardelli MB (2013) The high-throughput highway to computational materials design. Nat Mater 12:191–201. https://doi.org/10.1038/nmat356810.1038/nmat3568 ↗
29. Peng J, Yamamoto Y, Hawk JA (2020) Coupling physics in machine learning to predict properties of high-temperatures alloys. Npj Comput Mater 6:141. https://doi.org/10.1038/s41524-020-00407-210.1038/s41524-020-00407-2 ↗
30. Shen C, Wang C, Wei X (2019) Physical metallurgy-guided machine learning and artificial intelligent design of ultrahigh-strength stainless steel. Acta Mater 179:201–214. https://doi.org/10.1016/j.actamat.2019.08.03310.1016/j.actamat.2019.08.033 ↗
31. Hu M, Tan Q, Knibbe R (2024) Designing unique and high-performance Al alloys via machine learning: mitigating data bias through active learning. Comput Mater Sci 244:113204. https://doi.org/10.1016/j.commatsci.2024.11320410.1016/j.commatsci.2024.113204 ↗
32. Dong XX, Liu Q, Han WJ (2025) Intelligent development of high strength and ductile heat treatment-free Al-Si-Mg alloys for integrated die casting through the machine learning of experimental big data. J Alloy Compd 1021:179769. https://doi.org/10.1016/j.jallcom.2025.17976910.1016/j.jallcom.2025.179769 ↗
33. Jain S, Jain R, Dewangan S (2024) A machine learning perspective on hardness prediction in multicomponent Al-Mg based lightweight alloys. Mater Lett 365:136473. https://doi.org/10.1016/j.matlet.2024.13647310.1016/j.matlet.2024.136473 ↗
34. Juan YF, Niu G, Yang Y (2024) Accelerated design of Al-Zn-Mg-Cu alloys via machine learning. Trans Nonferrous Met Soc China 34:709–723. https://doi.org/10.1016/S1003-6326(23)66429-510.1016/S1003-6326(23)66429-5 ↗
35. Andersen SJ, Zandbergen HW, Jansen J (1998) The crystal structure of the β″ phase in Al-Mg-Si alloys. Acta Mater 46:3283–3298. https://doi.org/10.1016/S1359-6454(97)00493-X10.1016/S1359-6454(97)00493-X ↗
36. Wen T, Li ZC, Wang JY et al (2025) From crack-prone to crack-free: eliminating cracks in additively manufacturing of high-strength Mg2Si-modified Al-Mg-Si alloys. J Mater Sci Technol 204:276–291. https://doi.org/10.1016/j.matdes.2023.11202510.1016/j.matdes.2023.112025 ↗
37. Que Z, Wang Y, Fan Z (2018) Formation of the Fe-containing intermetallic compounds during solidification of Al-5Mg-2Si-0.7Mn-1.1Fe alloy. Metall Mater Trans A 49:2173–2181. https://doi.org/10.1007/s11661-018-4591-610.1007/s11661-018-4591-6 ↗
38. Ji SX, Yang WC, Gao F et al (2013) Effect of iron on the microstructure and mechanical property of Al-Mg-Si-Mn and Al-Mg-Si diecast alloys. Mater Sci Eng A 564:130–139. https://doi.org/10.1016/j.msea.2012.11.09510.1016/j.msea.2012.11.095 ↗
39. Hansen N (2004) Hall-Petch relation and boundary strengthening. Scr Mater 51:801–806. https://doi.org/10.1016/j.scriptamat.2004.06.00210.1016/j.scriptamat.2004.06.002 ↗
40. Myhr OR, Grong O, Andersen SJ (2001) Modelling of the age hardening behaviour of Al-Mg-Si alloys. Acta Mater 49:65–75. https://doi.org/10.1016/S1359-6454(00)00301-310.1016/S1359-6454(00)00301-3 ↗
41. Wang JY, Yang HL, Liu ZL et al (2024) Compositional regulation in additive manufacturing of precipitation-hardening (CoCrNi)94Ti3Al3 medium-entropy superalloy: cellular structure stabilization and strength enhancement. Compos B Eng 281:111570. https://doi.org/10.1016/j.compositesb.2024.11157010.1016/j.compositesb.2024.111570 ↗
42. Yang FP, Wang JY, Wen T et al (2024) Double-peak age strengthening of an Al-Mg-Si-Zn alloy processed by laser powder bed fusion. J Mater Sci Technol 192:82–94. https://doi.org/10.1016/j.jmst.2023.12.04010.1016/j.jmst.2023.12.040 ↗
43. Dong XX, Zhang YJ, Ji S (2017) Enhancement of mechanical properties in high silicon gravity cast AlSi9Mg alloy refined by Al3Ti3B master alloy. Mater Sci Eng A 700:291–300. https://doi.org/10.1016/j.msea.2017.06.00510.1016/j.msea.2017.06.005 ↗
44. Xiong T, Zheng S, Pang J et al (2020) High-strength and high-ductility AlCoCrFeNi2.1 eutectic high-entropy alloy achieved via precipitation strengthening in a heterogeneous structure. Scr Mater 186:336–340. https://doi.org/10.1016/j.scriptamat.2020.04.03510.1016/j.scriptamat.2020.04.035 ↗
45. Liu QL, Li XW, Xiao W et al (2024) Insights into precipitation characteristics and strengthening mechanisms in a low Cu/Mg ratio Al-Cu-Mg-Ag alloy. Mater Des 240:112836. https://doi.org/10.1016/j.matdes.2024.11283610.1016/j.matdes.2024.112836 ↗